Memory

37 practitioners working with Memory:

Agent Memory Systems How AI agents implement memory: short-term context, long-term storage, vector retrieval, and the architecture that ties it together.

AI Memory Compression Techniques for compressing AI observations into retrievable semantic summaries that fit in context windows

Build a Personal Knowledge Graph Connect your notes, projects, and contacts in a queryable graph. Entity extraction, Neo4j setup, and Obsidian graph visualization.

Building a Memory System Build persistent AI memory with Claude Code using episodic-memory MCP, memory files, and external tools like Obsidian and Notion

Building an AI Second Brain Transform AI from chatbot to persistent knowledge partner

Charles Packer — Building Machines That Learn and Remember creator of memgpt and co-founder of letta who pioneered llms as operating systems with virtual memory — enabling agents that truly remember

Clawlet AI agent with built-in semantic memory, one binary

cognitive debt, memory pattern, and devtools for agents three months of OpenClaw, SQLite as agent memory substrate, Chrome DevTools for non-human developers, and the hidden cost of AI velocity

cognitive debt: the hidden cost of AI velocity technical debt is code you can't maintain. cognitive debt is decisions you can't remember making. your AI agent ships fast — but are you taking out a loan you can't pay back?

context engineering context engineering is the discipline of crafting optimal context for AI agents — memory, retrieval, compression, and instruction design.

Context Rot: When More Tokens Mean Worse Results LLM performance degrades predictably as context windows fill up. Learn why this happens, how to detect it, and practical strategies to maintain output quality.

Context Window Management Keep your AI sharp by managing what fits in its working memory

Episodic Memory for LLM Agents Give AI agents memory of specific past events with temporal context. The missing piece between semantic facts and procedural rules in the CoALA framework.

failure-derived: AGENTS.md science, invisible configs, and who owns your model's behavior the first study of whether AGENTS.md files actually work, a silent A/B test reshaping Claude Code users' outcomes, a Pi Zero AI agent, and the sovereignty question hiding inside heretic's 891-star week

Graph Memory for Personal AI Knowledge graphs track relationships between people, projects, and time that vector databases miss. Build AI memory that understands context across sessions.

how to give ChatGPT long-term memory (the save game approach) a practical way to stop re-explaining yourself: build a simple, persistent memory layer for ChatGPT that survives new threads and new weeks.

Hybrid Retrieval: When RAG Meets Long Context Combine RAG retrieval with long-context windows strategically instead of treating them as competing approaches

infrastructure maturing, paradigms splitting context as filesystems, agents that self-evolve, red-teaming your prompts, the $100 ChatGPT, swarm intelligence engines, voice AI that never phones home, and LeCun's $1B bet against LLMs

Late Chunking: Context-Aware Document Splitting for Better Retrieval Process entire documents through embedding models before splitting to preserve cross-chunk context that traditional chunking destroys

Louis Beaumont Founder of Mediar AI and creator of screenpipe — 24/7 local screen and audio capture for AI memory. Building the open-source Rewind alternative.

Mem0 Mem0 — the open-source memory layer for AI agents. graph + vector memory, cross-session persistence, and why AI memory infrastructure matters.

Memory Attribution and Provenance Track where AI memories came from, when they were created, and how much to trust them

Memory Consolidation and Forgetting How AI agents consolidate short-term observations into long-term storage using sleep-inspired patterns, plus when and what to forget.

Preference Learning: AI That Adapts to You How AI systems infer your preferences from interactions and adapt without configuration. Covers POPI, Mem0, LaMP benchmarks, and building preference-aware systems.

Proactive AI Agent with Semantic Memory Turn your AI from reactive chatbot into proactive assistant using heartbeats, semantic search, and persistent memory.

Project Athena A save-game memory layer for ChatGPT that persists context, decisions, and state across 1,000+ sessions. Memory as infrastructure, not a feature.

Rowboat open-source AI coworker with persistent memory

save games, boundary leaks, and the self-hosted exodus a save-game memory layer for chatgpt, agents crossing permission lines, discord's face id panic, and skills becoming portable files.

Self-Updating Instructions (Procedural Memory) Build AI agents that modify their own operating instructions based on experience, feedback, and observed failures

Taranjeet Singh — Mem0 and the memory layer Taranjeet Singh, co-founder of Mem0, building the memory infrastructure for AI — graph + vector hybrid memory, and why every AI app will need a memory layer.

the memory problem: why your AI forgets everything by tuesday every AI assistant resets like goldfish. some people are fixing it. here's why it matters more than you think

trust is infrastructure now the personal AI ecosystem is moving past 'can it code' and building the hard parts: memory, security, and consent

trust is infrastructure now distillation scandals, safety standoffs, and the personal AI ecosystem building memory, security, and consent layers

your agent's memory is a filesystem now why treating AI memory as a file tree instead of a vector store changes everything

zvec lightweight, in-process vector database from Alibaba. your AI's memory layer without the infrastructure overhead.